Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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Hybrid BFPSO Approach for Effective Tuning of PID Controller for Load Frequency Control Application in an Interconnected Power System

  • Anbarasi, S. (Dept. of Electrical and Electronic Engineering, Mepco Schlenk Engineering College) ;
  • Muralidharan, S. (Dept. of Electrical and Electronic Engineering, Mepco Schlenk Engineering College)
  • Received : 2016.02.28
  • Accepted : 2017.02.17
  • Published : 2017.05.01
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Abstract

Penetration of renewable energy sources makes the modern interconnected power systems to have more intelligence and flexibility in the control. Hence, it is essential to maintain the system frequency and tie-line power exchange at nominal values using Load Frequency Control (LFC) for efficient, economic and reliable operation of power systems. In this paper, intelligent tuning of the Proportional Integral Derivative (PID) controller for LFC in an interconnected power system is considered as a main objective. The chosen problem is formulated as an optimization problem and the optimal gain parameters of PID controllers are computed with three innovative swarm intelligent algorithms named Particle Swarm Optimization (PSO), Bacterial Foraging Optimization Algorithm (BFOA) and hybrid Bacterial Foraging Particle Swarm Optimization (BFPSO) and a comparative study is made between them. A new objective function designed with necessary time domain specifications using weighted sum approach is also offered in this report and compared with conventional objective functions. All the simulation results clearly reveal that, the hybrid BFPSO tuned PID controller with proposed objective function has better control performances over other optimization methodologies.

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References

  1. Hassan Bevrani, Pourya Ranjbar Daneshmand, Poya Babahajyani, Yasunori Mitani and Takashi Hiyama, "Intelligent LFC Concerning High Penetration of Wind Power: Synthesis and Real-time Application," IEEE Transactions on Sustainable Energy, vol. 5 (2), pp. 655-662, 2013. https://doi.org/10.1109/TSTE.2013.2290126
  2. Hadi Saadat, Power system analysis: New York, Mc Graw-Hill, 1999.
  3. Katsuhiko Ogata, System dynamics: India, Pearson Education, 2008.
  4. Qing-Guo Wang, Zhen Ye, Wen-Jian Cai, Chang-Chieh Hang, "PID Control for Multi Variable Processes," Lecture notes in control and Information Science, Springer, pp. 1-5, 2008.
  5. Ahmad M. Hamza, Mohamed S. Saad. Hassan M. Rashad, Ahmed Bahgat, "Design of LFC and AVR for Single Area Power System with PID Controller Tuning By BFO and Ziegler Methods," International Journal of Computer Science and Telecommunications, vol. 4 (5), pp. 12-17, 2013.
  6. Hamed Shabani, Behrooz Vahidi, Majid Ebrahimpour, "A Robust PID Controller Based on Imperialist Competitive Algorithm for Load-frequency Control of Power Systems," ISA Transactions, vol. 52, pp. 88-95, 2013. https://doi.org/10.1016/j.isatra.2012.09.008
  7. Seyed Abbas Taher, Masoud Hajiakbari Fini, Saber Falahati Aliabadi, "Fractional Order PID Controller Design for LFC in Electric Power Systems using Imperialist Competitive Algorithm," Ain Shams Engineering Journal, vol. 5, pp. 121-135, 2014. https://doi.org/10.1016/j.asej.2013.07.006
  8. K. Naidu, H. Mokhlis, A. H. A. Bakar, "Multi Objective Optimization using Weighted Sum Artificial Bee Colony Algorithm for Load Frequency Control," International Journal of Electrical power and Energy systems, vol. 55, pp. 657-667, 2014. https://doi.org/10.1016/j.ijepes.2013.10.022
  9. Puja Dash, Lalit Chandra Saikia, Nidul Sinha, "Comparison of performances of several Cuckoo Search Algorithm Based 2DOF Controllers in AGC of Multiarea Thermal System," International Journal of Electrical power and Energy systems, vol. 55, pp. 429-436, 2014. https://doi.org/10.1016/j.ijepes.2013.09.034
  10. Ioan Cristian Trelea, "The Particle Swarm Optimization Algorithm: Convergence Analysis and Parameter Selection," Information Processing Letters, vol. 85, pp. 317-325 2003. https://doi.org/10.1016/S0020-0190(02)00447-7
  11. K. M. Passino, "Bacterial foraging optimization," International Journal of Swarm Intelligence Research, vol. 1 (1), pp. 1-16, 2010. https://doi.org/10.4018/jsir.2010010101
  12. E. S. Ali, S. M. Abd-Elazim, "BFOA Based Design of PID Controller for Two Area Load Frequency Control with Nonlinearities," International Journal of Electrical power and Energy systems, vol. 51, pp. 224-231 2013. https://doi.org/10.1016/j.ijepes.2013.02.030
  13. Anbarasi Soundarapandian, Muralidharan Srinivasan, "Application of Bacterial Foraging Optimization Algorithm for Improving Control and Stability," Technics Technologies Education Management, vol. 9 (2), pp. 479-486, 2014.
  14. S. M. Abd-Elazim, E. S. Ali, "A Hybrid Particle Swarm Optimization and Bacterial Foraging for Optimal Power System Stabilizers Design," International Journal of Electrical power and Energy systems, vol. 46, pp. 334-341, 2013. https://doi.org/10.1016/j.ijepes.2012.10.047
  15. Sidhartha Panda, Banaja Mohanty, P. K. Hotaa, "Hybrid BFOA-PSO Algorithm for Automatic Generation Control of Linear and Nonlinear Interconnected Power Systems," Applied Soft Computing, vol. 13, pp. 4718-4730, 2013. https://doi.org/10.1016/j.asoc.2013.07.021
  16. Dong Hwa Kim, "Hybrid GA-BF Based Intelligent PID Controller Tuning for AVR System," Applied Soft Computing, vol. 11, pp. 11-22, 2011. https://doi.org/10.1016/j.asoc.2009.01.004
  17. Haluk Gozde, Cengiz Taplamacioglu M, "Automatic Generation Control Application with Craziness Based Particle Swarm Optimization in a Thermal Power System," International Journal of Electrical power and Energy systems, vol. 33, pp. 8-16, 2011. https://doi.org/10.1016/j.ijepes.2010.08.010
  18. Rabindra Kumar Sahu, Sidhartha Panda, Umesh Kumar Rout, "DE Optimized Parallel 2-DOF PID Controller for Load Frequency Control of Power System with Governor Dead-band Nonlinearity", International Journal of Electrical power and Energy systems, vol. 49, pp. 19-33, 2013. https://doi.org/10.1016/j.ijepes.2012.12.009
  19. Swagatam Das, Arijit Biswas, Sambatra Dasgupta, Ajith Abraham, "Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications," Foundations of Computational Intelligence, vol. 3, pp. 23-55, 2009.
  20. W. M Korani, "Bacterial Foraging Oriented by Particle Swarm Optimization Strategy for PID Tuning," IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), Daejeon, pp. 445-450, 2009.
  21. K. N Vijayakumar, Power system network splitting and load frequency control optimization using ABC based algorithms: Thesis report, University of Malaya, 2015.

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